The Open Table-and-Text Question Answering (OTT-QA) dataset contains open questions which require retrieving tables and text from the web to answer. This dataset is re-annotated from the previous HybridQA dataset. The dataset is collected by UCSB NLP group and issued under MIT license.
Source: https://github.com/wenhuchen/OTT-QA
Image Source: https://github.com/wenhuchen/OTT-QA
Variants: OTT-QA
This dataset is used in 1 benchmark:
| Task | Model | Paper | Date |
|---|---|---|---|
| Question Answering | DoTTeR | Denoising Table-Text Retrieval for Open-Domain … | 2024-03-26 |
| Question Answering | CARP | Reasoning over Hybrid Chain for … | 2022-01-15 |
| Question Answering | Fusion Retriever+ETC | Open Question Answering over Tables … | 2020-10-20 |
Recent papers with results on this dataset: